• 제목/요약/키워드: features-extracting

검색결과 606건 처리시간 0.029초

접촉점에서의 국소 그래프 패턴에 의한 필기체 한글의 자소분리에 관한 연구 (A Study on the Phoneme Segmentation of Handwritten Korean Characters by Local Graph Patterns on Contacting Points)

  • 최필웅;이기영;구하성;고형화
    • 전자공학회논문지B
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    • 제30B권4호
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    • pp.1-10
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    • 1993
  • In this paper, a new method of phoneme segmentation of handwritten Korean characters using the local graph pattern is proposed. At first, thinning was performed before extracting features. End-point, inflexion-point, branch-point and cross-point were extracted as features. Using these features and the angular relations between these features, local graph pattern was made. When local graph pattern is made, the of strokes is investigated on contacting point. From this process, pattern is simplified as contacting pattern of the basic form and the contacting form we must take into account can be restricted within fixed region, 4therefore phoneme segmentation not influenced by characters form and any other contact in a single character is performed as matching this local graph pattern with base patterns searched ahead. This experiments with 540 characters have been conducted. From the result of this experiment, it is shown that phoneme segmentation is independent of characters form and other contact in a single character to obtain a correct segmentation rate of 95%, manages it efficiently to reduce the time spent in lock operation when the lock.

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피부 현미경 영상을 통한 피부 특징 추출 및 피부 나이 도출 기법 (A scheme of extracting age-related wrinkle feature and skin age based on dermoscopic images)

  • 최영환;황인준
    • 전기전자학회논문지
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    • 제14권4호
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    • pp.332-338
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    • 2010
  • 영상 처리를 통한 특징 추출은 영상 검색, 객체 인식, 영상 인덱싱을 포함하는 다양한 분야에서 전처리 과정으로 사용되어 왔다. 특히, 영상 질감 분석에서는 질감 특성 추출을 더 용이하게 하기 위해 질감의 대비를 증가시키는 방법을 사용한다. 생체 현미경 영상에서 두드러진 질감중의 하나는 주름이며 주름의 특징은 노화 관련 응용에 유용한 정보를 다양하게 제공한다. 본 논문에서는 피부 영상에서 나이 관련 특징을 추출하는 기존 방법을 개선하여 피부 나이 측정의 정확도를 높이는 방법을 제안한다.

가정환경을 위한 실용적인 SLAM 기법 개발 : 비전 센서와 초음파 센서의 통합 (A Practical Solution toward SLAM in Indoor environment Based on Visual Objects and Robust Sonar Features)

  • 안성환;최진우;최민용;정완균
    • 로봇학회논문지
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    • 제1권1호
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    • pp.25-35
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    • 2006
  • Improving practicality of SLAM requires various sensors to be fused effectively in order to cope with uncertainty induced from both environment and sensors. In this case, combining sonar and vision sensors possesses numerous advantages of economical efficiency and complementary cooperation. Especially, it can remedy false data association and divergence problem of sonar sensors, and overcome low frequency SLAM update caused by computational burden and weakness in illumination changes of vision sensors. In this paper, we propose a SLAM method to join sonar sensors and stereo camera together. It consists of two schemes, extracting robust point and line features from sonar data and recognizing planar visual objects using multi-scale Harris corner detector and its SIFT descriptor from pre-constructed object database. And fusing sonar features and visual objects through EKF-SLAM can give correct data association via object recognition and high frequency update via sonar features. As a result, it can increase robustness and accuracy of SLAM in indoor environment. The performance of the proposed algorithm was verified by experiments in home -like environment.

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Predicting numeric ratings for Google apps using text features and ensemble learning

  • Umer, Muhammad;Ashraf, Imran;Mehmood, Arif;Ullah, Saleem;Choi, Gyu Sang
    • ETRI Journal
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    • 제43권1호
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    • pp.95-108
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    • 2021
  • Application (app) ratings are feedback provided voluntarily by users and serve as important evaluation criteria for apps. However, these ratings can often be biased owing to insufficient or missing votes. Additionally, significant differences have been observed between numeric ratings and user reviews. This study aims to predict the numeric ratings of Google apps using machine learning classifiers. It exploits numeric app ratings provided by users as training data and returns authentic mobile app ratings by analyzing user reviews. An ensemble learning model is proposed for this purpose that considers term frequency/inverse document frequency (TF/IDF) features. Three TF/IDF features, including unigrams, bigrams, and trigrams, were used. The dataset was scraped from the Google Play store, extracting data from 14 different app categories. Biased and unbiased user ratings were discriminated using TextBlob analysis to formulate the ground truth, from which the classifier prediction accuracy was then evaluated. The results demonstrate the high potential for machine learning-based classifiers to predict authentic numeric ratings based on actual user reviews.

Image-based Extraction of Histogram Index for Concrete Crack Analysis

  • Kim, Bubryur;Lee, Dong-Eun
    • 국제학술발표논문집
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    • The 9th International Conference on Construction Engineering and Project Management
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    • pp.912-919
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    • 2022
  • The study is an image-based assessment that uses image processing techniques to determine the condition of concrete with surface cracks. The preparations of the dataset include resizing and image filtering to ensure statistical homogeneity and noise reduction. The image dataset is then segmented, making it more suited for extracting important features and easier to evaluate. The image is transformed into grayscale which removes the hue and saturation but retains the luminance. To create a clean edge map, the edge detection process is utilized to extract the major edge features of the image. The Otsu method is used to minimize intraclass variation between black and white pixels. Additionally, the median filter was employed to reduce noise while keeping the borders of the image. Image processing techniques are used to enhance the significant features of the concrete image, especially the defects. In this study, the tonal zones of the histogram and its properties are used to analyze the condition of the concrete. By examining the histogram, the viewer will be able to determine the information on the image through the number of pixels associated and each tonal characteristic on a graph. The features of the five tonal zones of the histogram which implies the qualities of the concrete image may be evaluated based on the quality of the contrast, brightness, highlights, shadow spikes, or the condition of the shadow region that corresponds to the foreground.

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비선형 특징추출을 위한 신경망의 학습성능 개선 (Improvement on Learning Performance of Neural Networks for Extracting Nonlinear Features)

  • 조용현;윤중환;성주원
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2000년도 추계학술대회 학술발표 논문집
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    • pp.77-80
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    • 2000
  • 본 논문에서는 새로운 학습알고리즘의 비선형 주요성분분석 신경망을 이용한 데이터의 효율적인 특징추출에 대하여 제안하였다. 제안된 학습알고리즘에서는 모멘트와 동적터널링을 조합하여 이용함으로써 최적해로의 수렴에 따른 발진을 억제하고 빠른 수렴속도로 전역최적해에 수렴되도록 학습시킬 수 있다. 제안된 학습알고리즘을 이용하여 128$\times$128 픽셀의 얼굴영상과 256$\times$128 픽셀의 자동차번호판 영상을 대상으로 시뮬레이션 한 결과, 기울기하강의 학습알고리즘을 이용한 기존 비선형 주요성분분석 신경망보다 우수한 수렴성능과 특징추출성능이 있음을 확인 할 수 있었다.

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효율적인 문서 자동 분류를 위한 대표 색인어 추출 기법 (A Feature Selection Technique for an Efficient Document Automatic Classification)

  • 김지숙;김영지;문현정;우용태
    • 정보기술과데이타베이스저널
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    • 제8권1호
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    • pp.117-128
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    • 2001
  • Recently there are many researches of text mining to find interesting patterns or association rules from mass textual documents. However, the words extracted from informal documents are tend to be irregular and there are too many general words, so if we use pre-exist method, we would have difficulty in retrieving knowledge information effectively. In this paper, we propose a new feature extraction method to classify mass documents using association rule based on unsupervised learning technique. In experiment, we show the efficiency of suggested method by extracting features and classifying of documents.

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등고선 지도로부터 특징 추출과 레이어 구성 (Feature extraction from contour map and construction of layer)

  • 최관순;이쾌희
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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    • pp.1169-1174
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    • 1991
  • In conventional geographic mapping system, it is needed to input many already existing geographic map into computer system for secure and efficient maintence. Because of large map data, it is required to construct layers from map image for easy display, fast retreval and efficient storage. Thus this paper represents a method of the extracting features from contour map and constructing three layers. The layers are symbol, building, contour line. Experimental results are presented confirming the method's high extraction.

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이미지 변환과 HMM에 기반한 자동 립리딩 (Automatic Lipreading Based on Image Transform and HMM)

  • 김진범;김진영
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1999년도 추계종합학술대회 논문집
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    • pp.585-588
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    • 1999
  • This paper concentrates on an experimental results on visual only recognition tasks using an image transform approach and HMM based recognition system. There are two approaches for extracting features of lipreading, a lip contour based approach and an image transform based one. The latter obtains a compressed representation of the image pixel values that contain the speaker's mouth results in superior lipreading performance. In addition, PCA(Principal component analysis) is used for fast algorithm. Finally, HMM recognition tasks are compared with the another.

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컴퓨터 화상처리를 이용한 차량번호판 추출방법 (An Extraction Medthod of Car Number Plates by Computer Picture Processing)

  • 崔亨振;吳永煥;Takeshi Agui;Masayuki Nakajima
    • 대한전자공학회논문지
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    • 제24권2호
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    • pp.309-314
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    • 1987
  • Using computer picture processing, a method of extracting the region of a car number plate is described. A modified Hough transformation, in which parameter plane is restricted, is proposed. The demerits of Hough transformation, i.e., it requires much computation time and storage capacity, are reduced by this method. Further, taking the features of a car number plate into consideration, the region of a car number plate is extracted.

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